Unveiling scholarly insights: A bibliometric analysis of literature on gender bias at the workplace
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.3.45Keywords:
Gender bias, Gender discrimination, Bibliometric analysis, Systematic literature review, Data visualization.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Gender bias and discrimination in the workplace remain significant global challenges, impacting individuals and organizations. Despite heightened awareness and scholarly focus, a comprehensive, up-to-date evaluation of the literature’s scientific impact and citation trends is missing. This research article addresses this gap through a bibliometric analysis from 2000 to 2023, assessing gender bias’s scientific significance, citations, and pre-publication information. Utilizing tools like RStudio, VOS viewer, Dimensions analytics, and MS Excel, the study analyzes manuscripts from the Dimensions database. The analysis reveals notable trends, showing a steady rise in publications from 2003, with fluctuations in 2002 and 2008-2011, stability from 2012-2015, and a significant surge from 2016-2023, peaking in 2019-2022. The United States leads in publication quantity and collaboration. Key topics such as "Economics and Identity," the "glass cliff phenomenon," and the "climate for women in academic science" dominate citations. Prominent journals like "Building A New Leadership Ladder" and "Plos One" highlight the interdisciplinary nature of gender bias research. Influential contributors like Geffner CJ, Kim S, and Ryan MK are acknowledged for their dedication. This study underscores the interdisciplinary reach of gender bias research across Human Society, Commerce, Law, Biomedical Sciences, and Psychology, offering valuable insights into publication trends, collaborative networks, and thematic developments. The findings emphasize the need for continued exploration and collaboration to address gender-related challenges in professional settings.Abstract
How to Cite
Downloads
Similar Articles
- Pravin P. P, J. Arunshankar, Development of digital twin for PMDC motor control loop , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Sindhu S, L. Arockiam, DRMF: Optimizing machine learning accuracy in IoT crop recommendation with domain rules and MissForest imputation , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- UMASHANKAR SHUKLA, ANIL K. UPADHYAY, MATHEMATICAL MODEL FOR INFECTION AND REMOVAL IN POPULATION , The Scientific Temper: Vol. 10 No. 1&2 (2019): The Scientific Temper
- Sweta Jain, Jacob Joseph Kalapurackal, Green Innovation, Pressure, Green Training, and Green Manufacturing: Empirical evidence from the Indian apparel export industry , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Shaik Abdulla P., Abdul Razak T., Retrieval-Based Inception V3-Net Algorithm and Invariant Data Classification using Enhanced Deep Belief Networks for Content-Based Image Retrieval , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Desalu Tamirat, Tesfaye Getachew , Worku masho, Zelalem Admasu , Morphological and morphometric features of indigenous chicken in North Shewa zone, Oromia regional state, Ethiopia , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Radha K. Jana, Dharmpal Singh, Saikat Maity, Modified firefly algorithm and different approaches for sentiment analysis , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Shane Desai, Bhaskar K. Pandya, Analyzing the Novels of T. S. Pillai and Perumal Murugan from Indian socio-political perspective , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- Tarannum ., Anuja Pandey, Arti Rauthan, An evaluation of the impact of lean management practices on patients’ satisfaction at a small healthcare facility , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Suprabha Amit Kshatriya, Arvind R Yadav, Early detection of fire and smoke using motion estimation algorithms utilizing machine learning , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 11 12 13 14 15 16 17 18 19 20 > >>
You may also start an advanced similarity search for this article.